DBMS > AllegroGraph vs. Apache Impala vs. ClickHouse vs. GridDB vs. TimescaleDB

System Properties Comparison AllegroGraph vs. Apache Impala vs. ClickHouse vs. GridDB vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Analytic DBMS for Hadoop

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Scalable in-memory time series database optimized for IoT and Big Data

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

impala.apache.org/impala-docs.html

clickhouse.com/docs

docs.griddb.net

docs.timescale.com

Developer

Franz Inc.

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Clickhouse Inc.

Toshiba Corporation

Timescale

Initial release

2004

2013

2016

2013

2017

Current release

8.0, December 2023

4.1.0, June 2022

v24.4.1.2088-stable, May 2024

5.1, August 2022

2.15.0, May 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS

Linux

Linux
OS X
Windows

Data scheme

yes

RDF schemas

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

bulk load of XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like DML and DDL statements

Close to ANSI SQL (SQL/JSON + extensions)

SQL92, SQL-like TQL (Toshiba Query Language)

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

user defined functions and integration of map-reduce

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

key based and custom

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.